activity
20242026
collaborators

5 papers

cond-mat.mes-hall2026

QDFlow: A Python package for physics simulations of quantum dot devices

Donovan L. Buterakos, Sandesh S. Kalantre, Joshua Ziegler +2

Recent advances in machine learning (ML) have accelerated progress in calibrating and operating quantum dot (QD) devices. However, most ML approaches rely on access to large, repre…

quant-ph2025

Operating two exchange-only qubits in parallel

Mateusz T. MÄ dzik, Florian Luthi, Gian Giacomo Guerreschi +38

Semiconductors are among the most promising platforms to implement large-scale quantum computers, as advanced manufacturing techniques allow fabrication of large quantum dot arrays…

cond-mat.mes-hall2025

End-to-End Analysis of Charge Stability Diagrams with Transformers

Rahul Marchand, Lucas Schorling, Cornelius Carlsson +8

Transformer models and end-to-end learning frameworks are rapidly revolutionizing the field of artificial intelligence. In this work, we apply object detection transformers to anal…

cond-mat.mes-hall2024

12-spin-qubit arrays fabricated on a 300 mm semiconductor manufacturing line

Hubert C. George, Mateusz T. MÄ dzik, Eric M. Henry +29

Intels efforts to build a practical quantum computer are focused on developing a scalable spin-qubit platform leveraging industrial high-volume semiconductor manufacturing expertis…

quant-ph2024

Probing single electrons across 300 mm spin qubit wafers

Samuel Neyens, Otto K. Zietz, Thomas F. Watson +27

Building a fault-tolerant quantum computer will require vast numbers of physical qubits. For qubit technologies based on solid state electronic devices, integrating millions of qub…